Digital Trust at Risk: Investigating the Rise of Fraud in AI-Driven Insurance Ecosystems

Abstract

Background: As InsurTech reshapes the global insurance industry through AI-powered underwriting, chatbot claims assistance, and data-driven personalization, it has simultaneously introduced new vulnerabilities. Fraudulent actors now exploit algorithmic loopholes, synthetic identities, and digital onboarding systems. The trade-off between automation efficiency and digital trust is becoming a central concern for insurers and regulators worldwide.
Objectives: This paper seeks to (1) identify how AI applications in insurance contribute to emerging fraud risks, (2) examine the role of trust in digital insurance interactions, and (3) offer a multi-layered governance and technical framework for minimizing fraud while enhancing consumer trust in InsurTech platforms.
Methods: A qualitative-quantitative hybrid design was adopted. A survey of 250 policyholders and 35 InsurTech professionals across Europe and Southeast Asia was conducted to measure perceived trust and fraud incidents. Case studies from five InsurTech startups were analyzed for fraud typologies and mitigation strategies. Thematic content analysis of regulatory reports from EIOPA, IRDAI, and NAIC supplemented the findings to evaluate compliance gaps and best practices.
Findings: The research highlights that AI-based decision-making lacks transparency, leading to blind spots that fraudsters exploit—particularly in identity verification and micro-claims. Firms investing in explainable AI (XAI), two-factor biometric onboarding, and real-time behavioral analytics reported significantly lower fraud exposure. Additionally, trust erosion due to claim rejections by opaque algorithms contributes to reputational risk. The study recommends an “AI-Fraud Governance Triad” model integrating ethics, transparency, and tech vigilance.